My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (1500+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(1500+页)和视频链接

Cron Job System

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

Source code for the blog post on the evolution of the asset allocation methods

Bayesian Deep Learning Benchmarks

Markov Decision Processes, Dynamic Programming and Reinforcement Learning

Simple Tensorflow Cookbook for easy-to-use

Monte Carlo Kernel Library

Projection predictive variable selection

TensorFlow Tutorials with YouTube Videos

Implementations of CNNs, RNNs and cool new techniques in deep learning from scratch

The C++ Core Guidelines are a set of tried-and-true guidelines, rules, and best practices about coding in C++

Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoo…

KDD CUP 2018

DTW (Dynamic Time Warping) python module

kdd2018 evaluation code

RStudio Cheat Sheets